How To Fuse Design And Data Intelligence With Human Experiences

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Experience is everywhere. From experiential marketing to user experience (UX) and customer experience (CX), the focus is on how a consumer is interacting with a brand or product. To have a full understanding of what experience a consumer would enjoy, you need to understand the data. Data-driven design is about using information gleaned from both quantitative and qualitative sources to inform how you make decisions for a set of users.

Facebook, Amazon and Apple are taking over in the digital era and housing some of the world’s most valuable data. They track consumer spending habits, behavior and preferences, all of which impact buying.

Data-driven decision (DDD) is the process of making decisions based on actual data, instead of just your own bias or experiences. Consumers have access to more information now than ever. It is easy to search for more information about a brand or process.

To create meaningful interactions and experiences for a consumer, understanding how they speak, how they interact with brands and how they purchase all impact your strategy to conversion. Whether you utilize data through design, press or marketing material, the same core function applies: interpreting data to benefit the overall bottom line.

There are dedicated positions, such as a data scientist, that are focused around analyzing, reporting and converting data for brands. The demand for these positions became larger when data-driven design and data-driven marketing became increasingly popular.

How Data Impacts Experience 

Millennials are jokingly best known for having student debt, being social media addicts and valuing experiences. Data tells us that millennials want to touch, feel and interact with brands and products rather than just be sold to. Stores of many big-box retailers such as Kmart and Sears have been closing, but utilizing data on consumer patterns could have avoided these massive losses and saved these household brands from being dismantled.

Forward-thinking companies such as Amazon are paying close attention to analytics and investment in the AI segment, which has helped it become the world’s largest retailer. Collaborations work because like-minded brands understand the value of data and adaptation in the marketplace. These influential partnerships bring data to the table that contributes to winning collaborations such as that between Kohl’s and Amazon.

Consumer data is collected through purchases and interactions to establish the patterns of that consumer and persona segmentation. This information helps make design decisions that resonate and create conversions that impact the overall bottom line for a company. It is important to understand how to collect the data that will influence the journeys and pathways to overall conversion.

Data is collected through user testing, consumer data on buying patterns, and interactions on brand and digital platforms. For example, social media platforms play a very large role in data collection. They are using that as a deliverable for brands to pay for and target specific targeted audiences based on the platform’s data collected on each user.

Collecting data may seem like a difficult task, but it is easier than you think. To start, one of the best tools we use at my agency to track user engagement and performance metrics is Google Analytics. Through website visits, bounce rate, location and demographics, we are able to tell how well a website is doing and determine areas of improvement. To create a successful brand and website design that is authentic, it is important to see the performance metrics to properly evaluate and analyze success. I also recommend data-collecting tools such as Moz, SEMrush, Crazy Egg and Kissmetrics. Many of these tools provide specific metrics that can be incorporated in the smart conversion funnels and help eliminate the guesswork of users’ expectations and behavior. We also often do in-person user group studies, and tools such as IPEVO and Tobii Pro help us record and measure hand gestures, eye movement and other biometrics. Nowadays, the majority of these mechanisms and software solutions are readily available through either engaging in experience lab sessions or self-deploying it in your organization.

The impact data has on a business is just one piece of the puzzle. Analyzing data assists in creating impactful interactions and meaningful conversions but also pushes a company to continue innovating and stay relevant in a noisy marketplace.

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Loknath Das